Prognostic Marker for Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Analysis of Diffusing Capacity of the Lung for Carbon Monoxide (DLCO) and Forced Expiratory Volume in One Second (FEV1)

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Prognostic Marker for Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Analysis of Diffusing Capacity of the Lung for Carbon Monoxide (D_LCO) and Forced Expiratory Volume in One Second (FEV₁)

https://doi.org/10.21203/rs.3.rs-96162/v1

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Background: It is important to assess the prognosis and classify patients in chronic obstructive pulmonary disease (COPD) and acute exacerbation of COPD (AECOPD) treatment. Recently, it was suggested that diffusing capacity of the lung for carbon monoxide (D_LCO) should be added to multidimensional tools for assessing COPD. This study aimed to compare the D_LCO and forced expiratory volume in one second (FEV₁)to identify better prognostic factors for admitted patients with AECOPD.

Methods: We retrospectively analyzed 342 patients with AECOPD receiving inpatient treatment. We classified 342 severe AECOPD events using D_LCO and FEV₁. We defined the prognostic factors of severe AECOPD as the length of hospital stay, mortality in hospital, experience of mechanical ventilation, and experience of intensive care unit (ICU) care. We analyzed the prognostic factors by multivariate analysis using logistic regression. In addition, we conducted a correlation analysis and receiver operating characteristic (ROC) curve analysis.

Results: In univariate and multivariate analyses, D_LCO was shown to predict mortality rate (odds ratio = 4.408; 95% confidence interval, 1.070–18.167; P = 0.040), experience of ventilator (odds ratio = 2.855; 95% confidence interval, 1.216–6.704; P = 0.016) and ICU (odds ratios = 2.685; 95% confidence interval, 1.290–5.590; P = 0.008). However, there was no statistically significant difference in mortality rate when using FEV₁ classification (P = 0.075). In the correlation analysis, both D_LCO and FEV₁ showed a negative correlation with length of hospital stay. The correlation rate was more pronounced in the D_LCO (D_LCO; B = -0.103, P < 0.001) (FEV₁; B = -0.075, P = 0.007). In addition, D_LCO showed better predictive ability than FEV₁in ROC curve analysis. The area under the curve (AUC) of D_LCO was greater than 0.68 for all prognostic factors, and in contrast, the AUC of FEV₁ was less than 0.68.

Conclusion: D_LCO was likely to be as good as or better prognostic marker than FEV₁ in severe AECOPD.

Pulmonology

Critical Care & Emergency Medicine

COPD

DLCO

FEV1

Chronic obstructive pulmonary disease (COPD) is a chronic airway disease defined by persistent respiratory symptoms and irreversible airflow limitation.^1–3 Patients with COPD present with various symptoms, such as cough, sputum, and dyspnea, and these symptoms are closely related to the quality of life and prognosis.^4,5 The global initiatives for chronic obstructive lung disease (GOLD) guidelines emphasize treatment based on patient history and symptoms, such as exacerbation history, the modified medical research council dyspnea scale (mMRC), and COPD assessment test (CAT).⁶ Forced expiratory volume in one second (FEV₁) is still used to grade the severity of airflow obstruction, but the 'refined ABCD assessment tool' excludes FEV₁ from the criteria for evaluating the 'ABCD' group. This is because the FEV₁ value is weakly correlated with the patient's symptoms and health status.^7,8 However, pulmonary function tests (PFT) are still important tests for diagnosing and treating COPD in the clinical field. Therefore, we want other PFT factors related to the patient's symptoms and health status rather than FEV₁. Several studies have shown that the diffusing capacity of the lung for carbon monoxide (D_LCO) among the various values of PFT is closely related to patient symptoms, prognosis, and oxygen demand in COPD.^9,10 In addition, there was a recent opinion that D_LCO should be added to multidimensional tools assessing COPD.¹¹ This study aimed to compare FEV₁ and D_LCO through the prognosis of severe acute exacerbations of COPD (AECOPD).

Subjects

We retrospectively analyzed the medical records of 342 patients admitted to Korea University Guro Hospital from January 2011 to May 2017. We searched our electronic medical records database with the keywords “COPD” and “Acute exacerbation.” This study was approved by the Guro Institutional Review Board. (KUGH16131-002). The requirement for informed consent from the patients was waived due to the retrospective nature of this study.

COPD was diagnosed based on the GOLD guidelines, where the ratio of FEV₁ to forced vital capacity (FVC) was less than 70% in post-bronchodilator spirometry and smokers with at least ten pack-years of tobacco exposure.⁶ AECOPD was defined as worsening of the patient’s respiratory symptoms beyond normal day-to-day variation. Severe AECOPD was defined as ‘if the patient needs hospitalization due to AECOPD.’ Baseline spirometry data used in the analysis were performed in a stable state without acute exacerbation for at least 1 month before admission. Patients were excluded with the following criteria: 1) the cause of admission was not AECOPD; for example, acute heart failure, acute pulmonary edema, acute pulmonary embolism, pneumothorax, and arrhythmia, 2) the patient had cancer, 3) the patient received a major operation within 3 months, 4) the patient had an acute coronary syndrome, brain hemorrhage, or brain infarction within 3 months, 5) the patient had previously been diagnosed with asthma, and 6) the patient had D_LCO results. All patients were 40 years old or older.

We classified 342 severe AECOPD events using D_LCO and FEV₁. When the D_LCO value is more than 50 (% of predicted value), it is defined as the 'D_LCO normal group' and when it is 50 (% of predicted value) or less, it is defined as the 'D_LCO impaired group.'¹¹ Likewise, when the FEV₁ value is more than 50 (% of predicted value), it is defined as the ‘FEV₁ normal group' and when it is 50 (% of predicted value) or less, it is defined as the ‘FEV₁ impaired group' (Fig. 1).

Data collection

We defined the prognostic factors of severe AECOPD as the length of hospital stay, mortality in hospital, experience of mechanical ventilation, and experience of intensive care unit (ICU) care in the hospital. When the patient was hospitalized more than once, only the first hospitalized events were included, and the others were excluded. The following medical data were analyzed: age, sex, smoking history, comorbidities, baseline spirometry, inhaler and oral medication before admission, length of hospital stay, hospital mortality, experience of mechanical ventilation, and experience of ICU care in hospital.

Statistical analysis

Data were analyzed using SPSS 20 software (SPSS for Windows, SPSS Inc., Chicago, IL, USA). Data are presented as average ± standard deviation or number (percentage). We performed a statistical analysis in two directions. First, two groups were classified using D_LCO and FEV₁ and analyzed statistically. Continuous variables were compared using the independent t-test, and categorical variables were compared using the chi-squared test. We analyzed the prognostic factors (except length of hospital stay) by multivariate analysis through logistic regression. Multivariate analysis was conducted for variables with a P-value of less than 0.05 in the univariate analysis, except for baseline spirometry (D_LCO and FEV₁). Multivariate analysis was conducted using a backward elimination procedure and was assessed by the Hosmer-Lemeshow test.

Second, the linear correlation between spirometry factors (D_LCO and FEV₁) and length of hospital stay were analyzed. In univariate analysis, the correlation coefficients between spirometry factors and length of hospital stay were analyzed using the Pearson correlation analysis. In addition, we performed a multivariate linear regression analysis that included variables with a P-value of less than 0.05 in the univariate analysis, except baseline spirometry. In addition, multivariate linear regression analysis was conducted using a backward elimination procedure. In the multivariate analysis, B was the regression coefficient, and a negative sign of the regression coefficient meant that the variables were negatively associated.

Third, we used receiver operating characteristic (ROC) curve analysis to predict the sensitivity and specificity of D_LCO and FEV₁ as prognostic markers in severe AECOPD. A P-value of less than 0.05 was considered statistically significant.

Baseline characteristics

Among the 342 events, the D_LCO normal group comprised 227 events (the D_LCO value was more than 50% of the predicted value), and 115 in the D_LCO impaired group. In the FEV₁ normal group (the FEV₁ value was more than 50% of the predicted value), there was 173 events, and the FEV₁ impaired group had 169 events. The average age was 71.5 ± 9.2 years. A total of 238 (69.6%) events were male and 104 (30.4%) were female. Sixty-three (18.4%) events were current smokers and the average pack/year history was 41.3 ± 17.1 years. A total of 225 (65.38) events were using inhalers, and 165 (48.2%) were taking respiratory-related oral medications. Averaged FEV₁ was 1.3 ± 0.5 L (54.0 ± 19.3%) and D_LCO was 10.6 ± 4.8 L (59.3 ± 21.4%). (Table 1) In both groups, the average length of hospital stay was 10.0 ± 5.1 days. The mortality rate was 11 (3.2%), the experience of ventilator care was 29 (8.5%), and the experience of ICU care was 39 (11.4%).

Table 1

Baseline characteristics of patients with AECOPD
	D_LCO Normal group (D_LCO > 50, n = 227)	D_LCO Impaired group (D_LCO ≤ 50, n = 115)	P-value	FEV₁ Normal group (FEV₁ > 50, n = 173)	FEV₁ Impaired group (FEV₁ ≤ 50, n = 169)	P-value	Total (n = 342)
Age (years)^†	71.1 ± 9.5	72.4 ± 8.6	0.223	72.7 ± 9.8	70.4 ± 8.5	0.023	71.5 ± 9.2
Sex, no. of exacerbations
Male^‡	144 (63.4%)	94 (81.7%)	0.001	105 (60.7%)	133 (78.7%)	< 0.001	238 (69.6%)
Female^‡	83 (36.6%)	21 (18.3%)		68 (39.3%)	36 (21.3%)		104 (30.4%)
Smoking history, no. of exacerbations
Current smoker^‡	42 (18.5%)	21 (18.3%)	0.957	32 (18.5%)	31 (18.3%)	0.971	63 (18.4%)
Ex-smoker^‡	185 (81.5%)	94 (81.7%)		141 (81.5)	138 (81.7%)		279 (81.6%)
Pack-year history^†	41.1 ± 16.8	41.8 ± 17.9	0.446	40.9 ± 16.5	41.7 ± 17.8	0.987
Comorbidities, no. of exacerbations
Hypertension^‡	111 (48.9%)	53 (46.1%)	0.623	85 (49.1%)	79 (46.7%)	0.659	164 (48.0%)
Diabetes^‡	54 (23.8%)	25 (21.7%)	0.671	43 (24.9%)	36 (21.3%)	0.436	49 (23.1%)
Previous TB history^‡	58 (25.6%)	43 (37.4%)	0.023	35 (20.2%)	66 (39.1%)	< 0.001	101 (29.5%)
Coronary artery disease^‡	37 (16.3%)	17 (14.8%)	0.716	32 (18.5%)	22 (13.0%)	0.165	54 (15.8%)
Cerebrovascular accident^‡	6 (2.6%)	9 (7.8%)	0.027	5 (2.9%)	10 (5.9%)	0.172	15 (4.4%)
Inhaler use before admission
LABAs^‡	2 (0.9%)	1 (0.9%)	0.015	2 (1.2%)	1 (0.6%)	< 0.001	3 (0.9%)
LAMAs^‡	24 (10.6%)	14 (12.2%)		27 (15.6%)	11 (6.5%)		38 (11.1%)
LABAs + LAMAs^‡	36 (15.9%)	16 (13.9%)		24 (13.9%)	28 (16.6%)		52 (15.2%)
ICS/LABAs^‡	25 (11.0%)	7 (6.1%)		21 (12.1%)	11 (6.5%)		32 (9.4%)
Triple therapy^‡	53 (23.3%)	47 (40.9%)		32 (18.5%)	68 (40.2%)		100 (29.2%)
None^‡	87 (38.3%)	30 (26.1%)		67 (38.7%)	50 (29.6%)		117 (34.2%)
Oral medication before admission
Oral β2 adrenoreceptor agonist^‡	8 (3.5%)	19 (16.5%)	< 0.001	9 (5.2%)	18 (10.7%)	0.062	27 (7.9%)
Roflumilast^‡	7 (3.1%)	10 (8.7%)	0.024	1 (0.6%)	16 (9.5%)	< 0.001	17 (5.0%)
Mucolytic agent^‡	92 (40.5%)	65 (56.5%)	0.005	68 (43.3%)	89 (52.7%)	0.013	157 (45.9%)
Oral steroids^‡	6 (2.6%)	2 (1.7%)	0.722	2 (1.2%)	6 (3.6%)	0.170	8 (2.3%)
Oral antibiotics^‡	7 (3.1%)	4 (3.5%)	1.000	3 (1.7%)	8 (4.7%)	0.116	11 (3.2%)
Baseline spirometry
FEV₁ (liters)^†	1.5 ± 0.5	1.1 ± 0.4	< 0.001	1.6 ± 0.5	1.0 ± 0.3	< 0.001	1.3 ± 0.5
FEV₁ (% of predicted value)^†	59.9 ± 18.1	42.1 ± 16.0	< 0.001	69.5 ± 13.6	38.0 ± 8.1	< 0.001	54.0 ± 19.3
D_LCO (liters)^†	12.5 ± 5.0	6.6 ± 2.2	< 0.001	11.9 ± 5.3	8.9 ± 4.1	< 0.001	10.6 ± 5.1
D_LCO (% of predicted value)^†	73.5 ± 16.4	38.7 ± 8.8	< 0.001	71.4 ± 20.4	52.0 ± 18.7	< 0.001	61.8 ± 21.8
^†Numbers are presented as mean ± standard deviation.
^‡Numbers are presented as n (%)
Abbreviations: AECOPD, acute exacerbations of chronic obstructive pulmonary disease; LABAs, long acting B agonist bronchodilator; LAMAs, long acting antimuscarinic agent bronchodilator; ICS, inhaled corticosteroids; FEV₁, forced expiratory volume in one second; D_LCO, diffusing capacity of the lung for carbon monoxide

Prognostic factor analysis classified using D_LCO and FEV₁

When classified through D_LCO, the D_LCO impaired group showed a poor prognosis in all four factors by univariate analysis (Fig. 2). When classified through FEV₁, the FEV₁ impaired group showed a poor prognosis in three factors by univariate analysis (Fig. 3). However, there was no statistically significant mortality rate when classified as FEV₁ (P-value = 0.116) (Fig. 3B).

In multivariate analysis, when classified as D_LCO, all three factors showed significant prognostic differences. In severe AECOPD, D_LCO has been shown to predict mortality rate, ventilator, and ICU possibilities. When classified as FEV₁, the experience of mechanical ventilation and ICU showed statistical significance. However, there was no significant difference in mortality rate (P = 0.075) (Table 2).

Table 2

Prognosis analysis for severe AECOPD
	Univariate analysis			Multivariate analysis
Parameter	D_LCO Normal group (D_LCO > 50, n = 227)	D_LCO Impaired group (D_LCO ≤ 50, n = 115)	P-value	Odds ratio	95% confidence interval	P-value
Mortality in hospital^‡	3 (1.3%)	8 (7.0%)	0.008	4.408	1.070-18.167	0.040
Mechanical ventilation^‡	11 (4.8%)	19 (15.7%)	0.001	2.855	1.216–6.704	0.016
Intensive care unit^‡	16 (7.0%)	23 (20.0%)	< 0.001	2.685	1.290–5.590	0.008
	FEV₁ Normal group (FEV₁ > 50, n = 173)	FEV₁ Impaired group (FEV₁ ≤ 50, n = 169)
Mortality in hospital^‡	3 (1.7%)	8 (4.7%)	0.116	4.633	0.858–25.036	0.075
Mechanical ventilation^‡	7 (4.0%)	22 (13.0%)	0.003	3.518	1.335–9.270	0.011
Intensive care unit^‡	9 (5.2%)	30 (17.8%)	< 0.001	4.527	1.886–10.869	0.001
^†Numbers are presented as mean ± standard deviation
^‡Numbers are presented as n (%)
Multivariate analysis was conducted for variables with a P-value of less than 0.05 in the univariate analysis, except for baseline spirometry.
Abbreviations: AECOPD, acute exacerbations of chronic obstructive pulmonary disease; FEV₁, forced expiratory volume in one second; D_LCO, diffusing capacity of the lung for carbon monoxide

Correlation analysis between spirometer factors and length of hospital stay

The length of hospital stay of the D_LCO normal group was 7.3 ± 5.0 days and the D_LCO impaired group was 12.4 ± 13.2 days. The length of hospital stay of the FEV₁ normal group was 7.7 ± 5.4 days and the FEV₁ impaired group was 10.4 ± 11.4 days. In the Pearson correlation analysis, both D_LCO and FEV₁ showed a negative correlation. The correlation coefficient was more pronounced in the D_LCO analysis. In multivariate linear regression analysis, both D_LCO and FEV₁ showed a negative correlation. Additionally, the regression coefficient was more pronounced in the D_LCO analysis (Table 3).

Table 3

Correlation analysis of length of hospital stay
			Univariate		Multivariate
Group	Number of events	Length of hospital stay (days)^†	Correlation coefficient	P-value	B	P-value
D_LCO Normal group (D_LCO > 50)	227	7.3 ± 5.0	-0.112	< 0.001	-0.103	< 0.001
D_LCO Impaired group (D_LCO ≤ 50)	115	12.4 ± 13.2
FEV₁ Normal group (FEV₁ > 50)	173	7.7 ± 5.4	-0.082	0.001	-0.075	0.007
FEV₁ Impaired group (FEV₁ ≤ 50)	169	10.4 ± 11.4
^†Numbers are presented as mean ± standard deviation.
Multivariate analysis was conducted for variables with a P-value of less than 0.05 in the univariate analysis, except for baseline spirometry.
B is the regression coefficient, and the negative sign of the regression coefficient means that the variables are negatively associated.
Abbreviations: FEV₁, forced expiratory volume in one second; D_LCO, diffusing capacity of the lung for carbon monoxide

ROC curve analysis of D_LCO and FEV₁

When analyzing the sensitivity and specificity using the ROC curve, D_LCO showed better predictive ability than FEV₁ (Table 4). When analyzing three prognostic factors (mortality in hospital, mechanical ventilation, and ICU care) through ROC curve analysis, area under the curve (AUC) was greater than 0.68 in all cases of D_LCO (Fig. 4). In contrast, the AUCs of FEV₁ were below 0.68 in all three prognostic factors. In addition, the sensitivity and specificity of D_LCO were more than 64.1%, which was generally higher than FEV₁.

Table 4

ROC curve analysis of D_LCO and FEV₁
Parameter	Prognostic factor	Optimal cut-off	Sensitivity	Specificity	AUC	P-value
Mortality in hospital	D_LCO	48.5	71.0	72.7	0.827	< 0.001
Mortality in hospital	FEV₁	45.5	63.1	63.6	0.621	0.173
Mechanical ventilation	D_LCO	51.5	68.4	65.5	0.717	< 0.001
Mechanical ventilation	FEV₁	44.5	66.5	65.5	0.675	0.002
Intensive care unit	D_LCO	53.5	65.0	64.1	0.682	< 0.001
Intensive care unit	FEV₁	46.5	63.0	64.1	0.652	0.002
Abbreviations: ROC, receiver operating characteristics; AUC, area under the curve; FEV₁, forced expiratory volume in one second; D_LCO, diffusing capacity of the lung for carbon monoxide

This is the first study to compare FEV₁ and D_LCO as prognostic markers in severe patients with AECOPD in Korea. In our study, the factors of prognosis were defined as the length of hospital stay, mortality rate in the hospital, experience of ventilation, and experience of ICU care. Classification by D_LCO showed significant differences in all prognostic factors. Classification by FEV₁ did not show a statistically significant mortality rate. In the correlation analysis, both D_LCO and FEV₁ showed a negative correlation with the length of hospital stay. The correlation coefficient was more pronounced in the D_LCO classification. In addition, when analyzing the ROC curve, D_LCO showed better predictive ability than FEV₁. Of course, some odds ratio values were better when classified as FEV₁ in our study. However, D_LCO was better in various analysis methods (correlation analysis, ROC curve analysis), which was likely to be as good as or better than FEV₁.

The PFT has various parameters. In general, we used FEV₁ to grade COPD and select the inhaler. In addition to FEV₁, D_LCO is an important prognostic factor. In a study of smokers who did not show an obstruction pattern in PFT, a low D_LCO group showed quickly decreased pulmonary function and COPD progression.¹² Studies have shown that D_LCO is a more accurate prognostic factor than FEV₁ when assessing postoperative risk.^13,14 In addition, D_LCO is known to accurately represent the actual emphysema level and performance status.^15,16 These results suggest that D_LCO can be a good predictor of early pulmonary dysfunction and prognosis.

If we know the prognosis of the patient early, we can focus on high-risk patients and improve the prognosis. The prognostic factors that can be used in the clinic are laboratory findings, scoring systems such as CAT or mMRC, and baseline spirometry.^17,18 In some studies, high-C-reactive protein, eosinopenia, and thrombocytopenia are associated with poor outcomes in AECOPD.^19–21 Although various scoring systems—such as St. George's Respiratory Questionnaire, mMRC, and CAT, are useful—patients with severe symptoms may not be graded or might have similar scores, making them difficult to use. Instead, we focused on baseline spirometry and confirmed that D_LCO is more accurate in evaluating the prognosis of hospitalized patients than FEV₁. If a grading system that considers both D_LCO and FEV₁ is developed, the prognosis can be predicted more accurately.

Our study was limited because it was a retrospective single-center study. In addition, the treatment received during the hospitalization period and the prognosis after discharge were not evaluated. Large prospective clinical studies that include information on treatment during hospitalization and postdischarge may be required.

D_LCO was likely to be as good as or better as a prognostic marker than FEV₁ in severe AECOPD. Accurate classification using D_LCO can help to shorten hospital stay, reduce ICU experience, and improve prognosis.

COPD: Chronic obstructive pulmonary disease

AECOPD: Acute exacerbation of chronic obstructive pulmonary disease

D_LCO: Diffusing capacity of the lung for carbon monoxide

FEV₁: Forced expiratory volume in one second

Ethics approval and consent to participate

This study was approved by the Guro Institutional Review Board. (KUGH16131-002).

Consent for publication

The requirement for informed consent from the patients was waived due to the retrospective nature of this study.

Availability of data and materials

Available.

Competing interests

There is no competing interest

Funding

There is no funding for this study.

Acknowledgments

This study was supported by a Korea University Guro Hospital Grant (O1801541)

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Prognostic Marker for Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Analysis of Diffusing Capacity of the Lung for Carbon Monoxide (D_LCO) and Forced Expiratory Volume in One Second (FEV₁)

Archived Versions:

Version 1

Abstract

Figures

Introduction

Method

Subjects

Data collection

Statistical analysis

Results

Baseline characteristics

Prognostic factor analysis classified using D_LCO and FEV₁

Correlation analysis between spirometer factors and length of hospital stay

ROC curve analysis of D_LCO and FEV₁

Discussion

Conclusion

Abbreviations

Declarations

References

Archived Versions:

Version 1

Prognostic Marker for Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Analysis of Diffusing Capacity of the Lung for Carbon Monoxide (DLCO) and Forced Expiratory Volume in One Second (FEV1)

Archived Versions:

Version 1

Abstract

Figures

Introduction

Method

Subjects

Data collection

Statistical analysis

Results

Baseline characteristics

Prognostic factor analysis classified using DLCO and FEV1

Correlation analysis between spirometer factors and length of hospital stay

ROC curve analysis of DLCO and FEV1

Discussion

Conclusion

Abbreviations

Declarations

References

Archived Versions:

Version 1

Prognostic Marker for Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Analysis of Diffusing Capacity of the Lung for Carbon Monoxide (D_LCO) and Forced Expiratory Volume in One Second (FEV₁)

Prognostic factor analysis classified using D_LCO and FEV₁

ROC curve analysis of D_LCO and FEV₁